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GeoServer Cookbook

By : Iacovella

4.8 (6)

GeoServer Cookbook

4.8 (6)

By: Iacovella

Overview of this book

This book is ideal for GIS experts, developers, and system administrators who have had a first glance at GeoServer and who are eager to explore all its features in order to configure professional map servers. Basic knowledge of GIS and GeoServer is required.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Sections

Conventions

Reader feedback

Customer support

Free Chapter

1. Working with Vectors

1. Working with Vectors

Introduction

Using different WFS versions in OpenLayers

Using WFS nonspatial filters

Using WFS spatial filters

Using WFS vendor parameters

Filtering data with CQL

Filtering data with CQL spatial operators

Creating a SQL view

Creating a parametric view

Improving performance with pregeneralized features

2. Working with Rasters

2. Working with Rasters

Introduction

Getting coverages in different formats

Using WCS vendor parameters

Publishing a mosaic

Using pyramids

Adding GDAL formats

Adding a PostGIS raster data source

3. Advanced Styling

3. Advanced Styling

Introduction

Installing the CSS module

Creating a simple polygon style with CSS

Adding filters to your style

Adding labels with CSS

Creating scale-dependent rules

Rendering transformations for raster data

Creating a dot density chart

4. Geoprocessing

4. Geoprocessing

Introduction

Installing the WPS module

Using the WPS process builder

Chaining process – selecting features contained in a polygon

Chaining process – building your own task

5. Advanced Configurations

5. Advanced Configurations

Introduction

Upgrading GeoServer

Creating a script for automatic startup

Optimizing Java

Setting up a JNDI connection pool

Working with CRS

Using the reprojection console

Overriding an official EPSG code

Setting up GeoWebCache – how to make pre-rendered tiles for high availability

Storing configurations in an RDBMS

6. Automating GeoServer Configurations

6. Automating GeoServer Configurations

Introduction

Managing workspaces with REST

Creating and editing data stores with REST

Managing layers with REST

Uploading and updating styles with REST

Managing layers with the GWC REST API

Managing cache tiles with the GWC REST API

7. Advanced Visualizations

7. Advanced Visualizations

Introduction

Adding time to WMS maps

Using the WMS animator

Keyhole Markup Language styling

Using z-order creatively

Using transparency creatively

Using symbology encoding

8. Monitoring and Tuning

8. Monitoring and Tuning

Introduction

Installing the control flow module

Setting a per-user limit

Setting a per-request limit

Installing the monitoring extension

Configuring the monitoring extension

Creating reports from the monitoring database

Limiting the GeoWebCache disk use

A. OGC for ESRI Professionals

A. OGC for ESRI Professionals

Introduction

ArcGIS versus GeoServer

Understanding standards

WMS versus the mapping service

WFS versus feature access

Publishing raster data with WCS

Index

Index

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Working with CRS

When working with spatial data, you should be aware of its features in order to avoid errors in its manipulation and representation. Among spatial data characteristics, a very important one is the Coordinate Reference System (CRS) that was originally used to define the data.

In this recipe, you will learn basic concepts about CRS and how to properly define them in GeoServer.

How to do it…

You need a new dataset for this recipe. We will use Texas counties' boundaries, freely available from U.S. Census Bureau. Go to http://www.census.gov/cgi-bin/geo/shapefiles2013/main, the main site to download the data from. Select the counties and click on the submit button.
From the states' list, select Texas and click on the Download button. When prompted, select a proper location on the filesystem to save the archive.
Unzip the archive. You'll find five files; have a look at the tl_2013_48_cousub.prj file. It contains a Well Known Text (WKT) representation of CRS for the data:
```
GEOGCS["GCS_North_American_1983...
```

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